Statystyczna Analiza Danych - Dr M. Nowak-Kępczyk
I. Dane podstawoweNazwa przedmiotu
Statystyczna Analiza Danych
Nazwa przedmiotu w języku angielskim Statistical Analysis of Data
Kierunek studiów Informatyka, matematyka
Poziom studiów (I, II, jednolite magisterskie) I
Forma studiów (stacjonarne, niestacjonarne) stacjonarne
Dyscyplina MATEMATYKA, INFORMATYKA
Język wykładowy ANGIELSKI
Koordynator przedmiotu/osoba odpowiedzialna dr Małgorzata Nowak-Kępczyk
Forma zajęć (katalog
zamknięty ze słownika) Liczba godzin semestr Punkty ECTS
wykład 30 2 or 4 or 6 5
konwersatorium
ćwiczenia 30 2 or 4 or 6
laboratorium warsztaty seminarium proseminarium lektorat praktyki
zajęcia terenowe pracownia dyplomowa translatorium
wizyta studyjna
Wymagania wstępne Elements of calculus. Basics of probabilistic methods.
II. Cele kształcenia dla przedmiotu
C1. The main aim of the course is to familiarize students with the methods and procedures of descriptive statistics and mathematical statistics.
C2. Students will get acquainted with the basic methods and objectives of descriptive statistics, such as the use of statistical measures, charts and methods of statistical inference, such as estimation and statistical testing principles.
III. Efekty uczenia się dla przedmiotu wraz z odniesieniem do efektów kierunkowych
Symbol Opis efektu przedmiotowego Odniesienie do efektu
kierunkowego WIEDZA
W_01 The student understands the importance of mathematics and its applications, in particular, its role in the context of contemporary civilization dilemmas.
K_W01
W_02 The student has advanced knowledge of the basic areas of higher mathematics, in particular in statistics and other selected fields of mathematics and its applications.
K_W04
UMIEJĘTNOŚCI
U_01 The student can employ statistical characteristics of population and
their sample analogues K_U35
U_02 The student is able to use his knowledge to formulate complex and unusual mathematical problems in a correct and
understandable way, discuss them and the methods of solving them and present mathematical results and contents, in particular using information and communication techniques.
K_U38
U_03 The student can determine parameters of distribution of random variable with discrete or continuous distribution; can apply limit theorems and laws of large numbers to estimate probabilities.
K_U33 KOMPETENCJE SPOŁECZNE
K_01 The student is prepared to appreciate the role and importance of knowledge in solving cognitive and practical problems, typical of occupations and workplaces appropriate for graduates in the field of mathematics/informatics and consulting experts in the case of difficulties in solving the problem
K_K02
K_02 Student is ready to present selected achievements of higher
mathematics in a popular way. K_K05
IV. Opis przedmiotu/ treści programowe
1. Main goals, advantages and disadvantages of statistics - examples of statistical problems, basic definitions (population, sample, random variable), measurement scales.
2. Basic statistical concepts - empirical distribution, data series, time series, types of data, quantity, cumulative quantity.
3. Measurements of descriptive statistics - average, median, quartiles, quintiles, standard deviation, variance, range. Other measures of descriptive statistics.
4. Statistical charts - histogram, side-and-must chart, pie chart, line chart, other charts.
5. Review of some distributions of random variables - discrete distributions and continuous distribution (binomial distribution, Poisson distribution, normal distribution, exponential distribution, Student\'s t- distribution).
6. Estimation - point estimation, estimator features, moment method, estimation of the maximum probability, methods and examples of interval estimation.
7. Statistical tests - the concept of zero hypothesis, alternative hypothesis, level of significance, types of errors, critical value. An example of statistical test tonnage.
8. Selected examples of statistical tests (chi-square tests, tests of means, Kolmogorov-Smirnov test, etc.).
9. Introduction to multidimensional analysis, concept of variable dependencies (covariance and correlation coefficient). Basics of regression analysis (linear and nonlinear).
10. Time series - smoothing time series, dynamics indicators. Discussion on the basics of forecasting time
11. Introduction to simulation methods - Monte Carlo method and its application.
V. Metody realizacji i weryfikacji efektów uczenia się Symbol
efektu Metody dydaktyczne
(lista wyboru)
Metody weryfikacji
(lista wyboru)
Sposoby dokumentacji
(lista wyboru)
WIEDZA
W_01 Problem lecture Test, written test, written
exam. Evaluated test.
W_02 Conventional lecture Test, written test, written
exam. Evaluated test.
W_…
UMIEJĘTNOŚCI
U_01 Guided practice Test. Evaluated test.
U_02 Guided practice Test, written test, written
exam. Evaluated test.
U_03 Guided practice Test, written test, written
exam. Evaluated test.
KOMPETENCJE SPOŁECZNE K_01 Conversational lecture Test, written test, written
exam. Evaluated test.
K_02 Group work, work in pairs Test, written test, written
exam. Evaluated test.
K_...
LECTURE
The completion of classes is required.
Based on written exam:
86 – 100% (5,0) 76 – 85% (4,5) 66 – 76% (4,0) 60 – 65% (3,5) 50 – 59% (3,0) less than 50% (2,0) CLASSES:
80% of attendance is required.
Final grade based on two tests:
86 – 100% (5,0) 76 – 85% (4,5) 66 – 76% (4,0) 60 – 65% (3,5) 50 – 59% (3,0) less than 50% (2,0)
The detailed description of assessment is given during the lecture/classes.
Forma aktywności studenta Liczba godzin Liczba godzin kontaktowych z nauczycielem 90
Liczba godzin indywidualnej pracy studenta 60
VII. Literatura Literatura podstawowa
1) William Mendenhall, Robert J. Beaver, Barbara M. Beaver “Introduction to Probability and Statistics”
2) David Freedman, Robert Pisani, Roger Pruves “Statistics” Viva Books, 2011 3) Andrzej Stanisz, "Przystępny kurs statystyki", Kraków 2001
4) Amir D. Aczel “Complete business statistics” Wohl Publishing; 8th edition (2012) Literatura uzupełniająca
1) Starzyńska W., Statystyka praktyczna. Wydawnictwo naukowe PWN, Warszawa 2002 i wydania późniejsze
2) Ostasiewicz S., Rusnak Z., Siedlecka U.., Statystyka. Elemety teorii i zadania. Wydanie 4, poprawione. Wydawnictwo Akademii Ekonomicznej we Wrocławiu, Wrocław 2001.
3) Sobczyk M., Statystyka. PWN, Warszawa 2001 i późniejsze wydania.
4) Roxy Peck, Chris Olsen, Jay Devore “Introduction to Statistics and Data Analysis” Cengage Learning, Jan 1, 2011
